• The Korean Journal of Franchise Management
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• v.8 no.4
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• pp.33-43
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• 2017

Purpose - Previous studies about corporate image generally explore how corporate image affects a company's effectiveness from the consumer view. However this study attempts to explore the impacts of corporate image (reliability, friendly, corporate social responsibility, and innovation) on employees' altruistic behaviors in the franchise industry context. This study also examine whether organizational trust and affective commitment play a mediating role in the relationship between corporate image and employees' altruistic behaviors. The authors developed several hypotheses to achieve these purposes. Research design, data, and methodology - The data were collected from employees in food-service franchise companies located in Seoul, Korea. Among a total of 363 questionnaires distributed, 294(response rate of 81%) questionnaires were returned. After excluding 18 invalid respondent questionnaires, 276 valid questionnaires(response rate of 76%) were coded and analyzed using frequency, confirmatory factor analysis, correlations analysis, and structural equation modeling with SPSS 21 and SmartPLS 3.0. Result - The findings of the study are as follows: First, friendly, CSR, and innovation had positive effects on organizational trust, but reliability did not have a significant effect on organizational trust. Second, reliability and friendly of corporate image had positive effects on affective commitment, but CSR and innovation did have a significant effect on affective commitment. Third, organizational trust and affective commitment had positive effects on employees' altruistic behaviors. Conclusions - The aim of this study is to investigate the franchise corporate image as a significant influencing factor of employees' altruistic behaviors. The data were collected from only employees from franchising companies. The findings might vary from position to position. Future studies need to collect and compare data from managers. Future studies need to consider other variables that affect employees' altruistic behaviors. For example, leadership and market orientation might influence employees' attitude and behaviors. Also, future research should include other variables and it may have limitations in sample representative because of sampling franchise corporate in Seoul. Future studies will include franchise corporate all over the country. Future studies can also consider other variables (e.g., job performance and turnover intentions) to measure employee performance at the level of individuals and identify the impact of employee performance on business performance at the level of corporate.

• Journal of the Korean Society of Costume
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• v.58 no.2
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• pp.107-119
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• 2008

This study aims to define the concept of the futuristic image in fashion since 2000. In this study, earlier studies of the futuristic images in the fashion are analyzed and it is discovered that the most important characteristics of the futuristic images are the cosmic space and virtual reality. An analysis of actual data of the futuristic images of the fashion since 2000 produces the following conclusions. First, since 2000 the futuristic fashion to convey the image of space tends to be minimalist, taking H or A silhouette and using white, silver, or other vivid colors. Second, since 2000 the image of virtual reality is often expressed in the fashion of futuristic image as female fighters or vampires of the future who mostly wear pants suit or skirts that expose the body line. Materials of advanced technology or shiny leather are often used and dark colors including black are dominant in these images. Third, when the space image is expressed, the androgynous youth is emphasized. However when female fighters or vampires of the future are shown, sexual image of gloomy atmosphere is often stressed. Fourth, the fashion of futuristic image since 2000 takes up the space age look of the 1960s and the techno-cyber look of the 1980s and the 1990s. However their internal meanings are lost and only external forms are repeated. In sum, the current fashion of futuristic image emulates the past look of the fashion which was circulated as futuristic images and may be considered as a result of combination of futuristic image and retrospective image.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.718-721
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• 1988

In this paper, we develop 256*256*8 bit real-time image digitizer with the IBM-PC as a image processor. With this developed system, we process a chest X-ray image, which is a medical image, using the adaptive algorithm. In the future, we consider that the application of this developed system is extended in the various fields.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1332-1335
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• 1996

It is very important to predict the future position for the heavy vehicle with evasive maneuvering. In this paper, we considered for the manual image tracking system. The vehicle images are received from gyro stabilized mirror system, pass through the optical lens, processed, and displayed on the TV monitor. The operator try to lay the reticle to the center of vehicle image. When the vehicle is moving, the mirror platform (actually the line of sight) should follow the vehicle and the angular rate information is picked up from the mirror stabilized system. This rate signal should be used to predict the future vehicle position. The problem is that the visual system of the human operator is in the closed loop system. The rate signals are disturbed by the operator. In addition, there are some non linearities concerned with the control handle bar and the servo control system. The proposed Kalman filter, combined with some modifications for operator disturbance rejection, improved the predication of the future vehicle position when compared with the conventional passive filter used.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1228-1248
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• 2020

Steganalysis & steganography have witnessed immense progress over the past few years by the advancement of deep convolutional neural networks (DCNN). In this paper, we analyzed current research states from the latest image steganography and steganalysis frameworks based on deep learning. Our objective is to provide for future researchers the work being done on deep learning-based image steganography & steganalysis and highlights the strengths and weakness of existing up-to-date techniques. The result of this study opens new approaches for upcoming research and may serve as source of hypothesis for further significant research on deep learning-based image steganography and steganalysis. Finally, technical challenges of current methods and several promising directions on deep learning steganography and steganalysis are suggested to illustrate how these challenges can be transferred into prolific future research avenues.

• Proceedings of the KSRS Conference
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• v.1
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• pp.260-262
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• 2006

One of future remote sensing techniques for transportation application is vehicle detection from the space, which could be the basis of measuring traffic volume and recognizing traffic condition in the future. This paper introduces an approach to vehicle detection using image object segmentation approach. The object-oriented image processing is particularly beneficial to high-resolution image classification of urban area, which suffers from noisy components in general. The project site was Dae-Jeon metropolitan area and a set of true color aerial images at 10cm resolution was used for the test. Authors investigated a variety of parameters such as scale, color, and shape and produced a customized solution for vehicle detection, which is based on a knowledge-based hierarchical model in the environment of eCognition. The highest tumbling block of the vehicle detection in the given data sets was to discriminate vehicles in dark color from new black asphalt pavement. Except for the cases, the overall accuracy was over 90%.

• Journal of the Korea Society of Computer and Information
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• v.23 no.1
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• pp.33-39
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• 2018

In this paper, We studied the possibility of SoC(System On Chip) design using infrared image processing IP(Intellectual Property). And, we studied NUC(Non Uniformity Correction), BPR(Bad Pixel Recovery), and CEM(Contrast Enhancement) processing, the infrared image processing algorithm implemented by IP. We showed the logic and timing diagram implemented through the hardware block designed based on each algorithm. Each algorithm was coded as RTL(Register Transfer Level) using Verilog HDL(Hardware Description Language), ALTERA QUARTUS synthesis, and programed in FPGA(Field Programmable Gated Array). In addition, we have verified that the image data is processed at each algorithm without any problems by integrating the infrared image processing algorithm. Particularly, using the directly manufactured electronic board, Processor, SRAM, and FLASH are interconnected and tested and the verification result is presented so that the SoC type can be realized later. The infrared image processing IP proposed and verified in this study is expected to be of high value in the future SoC semiconductor fabrication. In addition, we have laid the basis for future application in the camera SoC industry.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.445-446
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• 2006

This paper is concerned with a substantial speed up of image processing methods and less power consumption on 2D images making use of modern FPGA (Field Programmable Gate Array) technology. We implemented 2D FFT and edge detection algorithms based on FPGA and examined processing time and power consumption compared with C/C++ and Alti-Vec technologies.

• Broadcasting and Media Magazine
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• v.5 no.1
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• pp.59-71
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• 2000

This paper presents a survey of the CMOs-based image sensor and its applications to various real field digital camera. CMOS image sensor, called active pixel sensor (APS), has many interesting properties such ash I회 sensitivity, high speed readout, random access and lower power consumption when it is compared with CCd. this paper also addresses the state-of-the-art of CMOS image sensor, and gives some examples of its application to digital camera and special-purpose cameras. with the advancement of semiconductor technology, CMOS image sensor is a future technology for imaging system, and will be widely used in the filed of image capturing for consumer electronics and scientific measurements.

• The Journal of the Korea Contents Association
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• v.20 no.7
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• pp.86-96
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• 2020

Based on the use cases of image recognition technology, this study looked at how artificial intelligence plays a role in image recognition technology. Through image recognition technology, satellite images can be analyzed with artificial intelligence to reveal the calculation of oil storage tanks in certain countries. And image recognition technology makes it possible for searching images or products similar to images taken or downloaded by users, as well as arranging fruit yields, or detecting plant diseases. Based on deep learning and neural network algorithms, we can recognize people's age, gender, and mood, confirming that image recognition technology is being applied in various industries. In this study, we can look at the use cases of domestic and overseas image recognition technology, as well as see which methods are being applied to the industry. In addition, through this study, the direction of future research was presented, focusing on various successful cases in which image recognition technology was implemented and applied in various industries. At the conclusion, it can be considered that the direction in which domestic image recognition technology should move forward in the future.